Pervasive and Mobile Computing最新文献

{"title":"SmartSPEC: A framework to generate customizable, semantics-based smart space datasets","authors":"Andrew Chio ,&nbsp;Daokun Jiang ,&nbsp;Peeyush Gupta ,&nbsp;Georgios Bouloukakis ,&nbsp;Roberto Yus ,&nbsp;Sharad Mehrotra ,&nbsp;Nalini Venkatasubramanian","doi":"10.1016/j.pmcj.2023.101809","DOIUrl":"https://doi.org/10.1016/j.pmcj.2023.101809","url":null,"abstract":"<div><p>This paper presents SmartSPEC, an approach to generate customizable synthetic smart space datasets using sensorized spaces in which people and events are embedded. Smart space datasets are critical to design, deploy and evaluate systems and applications under issues of heterogeneity, scalability and robustness, leading to cost-effective operation which improves the safety, comfort and convenience experienced by space occupants. However, many challenges exist in obtaining realistic smart space datasets for testing and validation, from a lack of fine-grained sensing to privacy/security concerns. SmartSPEC is a smart space simulator and data generator that leverages a semantic model augmented with user-defined constraints to represent important attributes, relationships, and external domain knowledge for a smart space. We employ machine learning (ML) approaches to extract relevant patterns from a sensorized space, which are used in an event-driven simulation strategy to generate realistic simulated data about the space (events, trajectories, sensor observation datasets, etc.). To evaluate the realism of the generated data, we develop a structured methodology and metrics to assess various aspects of smart space datasets, including trajectories of people and occupancy of spaces. Our experimental study looks at two real-world settings/datasets: an instrumented smart campus building and a city-wide GPS dataset. Our results show the realism of trajectories produced by SmartSPEC (<span><math><mrow><mn>1</mn><mo>.</mo><mn>4</mn><mi>x</mi></mrow></math></span> to <span><math><mrow><mn>4</mn><mo>.</mo><mn>4</mn><mi>x</mi></mrow></math></span> more realistic than the best synthetic data baseline when compared to real-world data, depending on the scenario and configuration), as well as sensor data derived from such trajectories which adhere to the underlying semantics of the smart space as compared to synthetic sensor data baselines, even under hypothetical changes.</p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49741016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fog-ROCL: A Fog based RSU Optimum Configuration and Localization in VANETs","authors":"Rehab Shahin, S. Saif, A. El-Moursy, H. Abbas, S. Nassar","doi":"10.1016/j.pmcj.2023.101807","DOIUrl":"https://doi.org/10.1016/j.pmcj.2023.101807","url":null,"abstract":"","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54901900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Balancing local vs. remote state allocation for micro-services in the cloud-edge continuum","authors":"C. Puliafito, C. Cicconetti, M. Conti, E. Mingozzi, Andrea Passarella","doi":"10.1016/j.pmcj.2023.101808","DOIUrl":"https://doi.org/10.1016/j.pmcj.2023.101808","url":null,"abstract":"","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54901905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IoT systems with multi-tier, distributed intelligence: From architecture to prototype","authors":"Nada GabAllah ,&nbsp;Ibrahim Farrag ,&nbsp;Ramy Khalil ,&nbsp;Hossam Sharara ,&nbsp;Tamer ElBatt","doi":"10.1016/j.pmcj.2023.101818","DOIUrl":"https://doi.org/10.1016/j.pmcj.2023.101818","url":null,"abstract":"<div><p><span><span>In this paper, we propose an architecture, design and build a prototype of a novel IoT system with intelligence, distributed at multiple tiers including the network edge. Our proposed architecture hosts a modular, three-tier IoT system including the edge, gateway (fog) and cloud tiers. The proposed system relies on data acquired by edge devices to realize a distributed </span>machine learning model and achieve timely response at the edge using a lightweight machine learning model. In addition, it employs more sophisticated machine learning models at the higher fog and cloud tiers for wider-scope, long-term decision making. One of the prime objectives of the proposed system is reducing the volume of data transferred across tiers. This is attained through intelligent data filtering at the edge/gateway tiers to distill key events that avail the most relevant data points to higher-tier machine learning models at the gateway and cloud. This, in turn, reduces the outliers and the redundant data that may impact the gateway and cloud models and reduces the inter-tier </span>communications overhead<span>. To demonstrate the merits of our proposed system, we build a proof-of-concept prototype hosting the three tiers, using COTS components and supporting networking technologies. We demonstrate through extensive experiments the merits of the proposed system. A major finding is that our system is capable of achieving prediction performance comparable to the centralized machine learning baseline model, while reducing the inter-tier communications overhead by up to 80%.</span></p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49740418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Online continual learning for human activity recognition","authors":"Martin Schiemer,&nbsp;Lei Fang,&nbsp;Simon Dobson,&nbsp;Juan Ye","doi":"10.1016/j.pmcj.2023.101817","DOIUrl":"https://doi.org/10.1016/j.pmcj.2023.101817","url":null,"abstract":"<div><p>Sensor-based human activity recognition (HAR), with the ability to recognise human activities from wearable or embedded sensors, has been playing an important role in many applications including personal health monitoring, smart home, and manufacturing. The real-world, long-term deployment of these HAR systems drives a critical research question: <em>how to evolve the HAR model automatically over time to accommodate changes in an environment or activity patterns</em>. This paper presents an online continual learning (OCL) scenario for HAR, where sensor data arrives in a streaming manner which contains unlabelled samples from already learnt activities or new activities. We propose a technique, OCL-HAR, making a real-time prediction on the streaming sensor data while at the same time discovering and learning new activities. We have empirically evaluated OCL-HAR on four third-party, publicly available HAR datasets. Our results have shown that this OCL scenario is challenging to state-of-the-art continual learning techniques that have significantly underperformed. Our technique OCL-HAR has consistently outperformed them in all experiment setups, leading up to 0.17 and 0.23 improvements in micro and macro F1 scores.</p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49740367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IoT systems with multi-tier, distributed intelligence: From architecture to prototype","authors":"Nada A. GabAllah, Ibrahim Farrag, Ramy Khalil, Hossam Sharara, T. Elbatt","doi":"10.1016/j.pmcj.2023.101818","DOIUrl":"https://doi.org/10.1016/j.pmcj.2023.101818","url":null,"abstract":"","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54901925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Embedded federated learning over a LoRa mesh network","authors":"Nil Llisterri Giménez, J. M. Solé, Felix Freitag","doi":"10.1016/j.pmcj.2023.101819","DOIUrl":"https://doi.org/10.1016/j.pmcj.2023.101819","url":null,"abstract":"","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54901945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SmartSPEC: A framework to generate customizable, semantics-based smart space datasets","authors":"Andrew Chio, Daokun Jiang, Peeyush Gupta, Georgios Bouloukakis, Roberto Yus, S. Mehrotra, N. Venkatasubramanian","doi":"10.1016/j.pmcj.2023.101809","DOIUrl":"https://doi.org/10.1016/j.pmcj.2023.101809","url":null,"abstract":"","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54901913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wireless power transfer with unmanned aerial vehicles: State of the art and open challenges","authors":"Tamoghna Ojha ,&nbsp;Theofanis P. Raptis ,&nbsp;Andrea Passarella ,&nbsp;Marco Conti","doi":"10.1016/j.pmcj.2023.101820","DOIUrl":"https://doi.org/10.1016/j.pmcj.2023.101820","url":null,"abstract":"<div><p><span>Wireless power transfer (WPT) techniques are emerging as a fundamental component of next-generation </span>energy management<span><span> in mobile networks. In this context, the use of UAVs opens many possibilities, either using them as mobile </span>energy storage devices<span> to recharge IoT nodes, or to prolong their operation time via smart charging themselves at ground stations. This paper surveys the recent literature on WPT as it applies to UAVs and identifies several open research challenges for the future. As a first step, we tessellate the related research corpus in four fundamental categories (architectures, power and communications enabling technologies, optimization with respect to spatial concepts, optimization of operational aspects). Second, for each category, we provide a critical review of the recent WPT UAV approaches with respect to the way they specialize the general concept of WPT and the extent of their applicability. The survey presents the latest advances in WPT UAV methodologies and related energy-centric services, spanning all the way from the communications aspects deep in the small- and large-scale deployments, up to the operational and applications aspects. Finally, motivated by the rich conclusions of this critical analysis, we identify open challenges for future research. Our approach is horizontal, as the selected publications were drawn from across all vertical areas of research on UAVs. This paper can help the readers to deeply understand how WPT is currently applied to UAVs, and select interesting open research opportunities to pursue.</span></span></p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49740419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Balancing local vs. remote state allocation for micro-services in the cloud–edge continuum","authors":"Carlo Puliafito ,&nbsp;Claudio Cicconetti ,&nbsp;Marco Conti ,&nbsp;Enzo Mingozzi ,&nbsp;Andrea Passarella","doi":"10.1016/j.pmcj.2023.101808","DOIUrl":"https://doi.org/10.1016/j.pmcj.2023.101808","url":null,"abstract":"<div><p>In the world of cloud technologies, serverless computing has now settled as a stable and promising resident. This gives a cloud provider the flexibility to provide its users with both Platform-as-a-Service (PaaS), i.e., the back-end application runs in a dedicated container, or Function-as-a-Service (FaaS), i.e., the back-end logic is offered as elementary functions that are invoked by the client applications. In parallel, edge computing has attracted a significant interest, due its enticing promises of reducing the outbound traffic of telco operators, while at the same time cutting down the user latency. As a result, in the near future, PaaS and FaaS containers are going to cohabit in a versatile computation infrastructure spanning from the far edge up to the cloud. In this paper we propose a mathematical formulation of a resource allocation problem that optimizes the assignment of both types of containers and can be solved efficiently by an edge orchestrator. We evaluate the proposed solution via extensive simulation experiments, which show that our approach, which takes into account the characteristics of PaaS vs. FaaS, provides significant performance benefits compared to less sophisticated strategies, despite its relatively low run-time complexity.</p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49740741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}